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Lai, Morris K. – 1974
When analysis of variance is used, statistically significant differences may or may not be of practical significance to educators. A large part of the problem is due to the fact that a "zero difference" null hypothesis can always be rejected statistically if the sample size is large enough. If, however, a method based on the noncentral F…
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Mathematical Models
PDF pending restorationSchluck, Gerald J.
Statistical methods that can be applied in the sequential analysis of multivariate empirical data are provided. Twenty-three specific formulas for use under varying conditions are discussed. A historical sketch of sequential analysis since World War II and a bibliography are included. (AE)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Mathematical Applications
SAW, J.G. – 1964
THIS PAPER DEALS WITH SOME TESTS OF HYPOTHESIS FREQUENTLY ENCOUNTERED IN THE ANALYSIS OF MULTIVARIATE DATA. THE TYPE OF HYPOTHESIS CONSIDERED IS THAT WHICH THE STATISTICIAN CAN ANSWER IN THE NEGATIVE OR AFFIRMATIVE. THE DOOLITTLE METHOD MAKES IT POSSIBLE TO EVALUATE THE DETERMINANT OF A MATRIX OF HIGH ORDER, TO SOLVE A MATRIX EQUATION, OR TO…
Descriptors: Analysis of Variance, Classification, Data Analysis, Hypothesis Testing
Folsom, Ralph E., Jr. – 1975
This memorandum demonstrates a variance components methodology for partitioning the overall design effect (D) for a ratio mean into stratification (S), unequal weighting (W), and clustering (C) effects, so that D = WSC. In section 2, a sample selection scheme modeled after the National Longitudinal Study of the High School Class of 1972 (NKS)…
Descriptors: Analysis of Variance, Cluster Analysis, Followup Studies, Graduate Surveys


